Xu Jialin, Audet Charles, DiLiberti Charles E, Hauck Walter W, Montague Timothy H, Parr Alan F, Potvin Diane, Schuirmann Donald J
Merck & Co., Inc.,, Upper Gwynedd, PA,, USA.
GERAD and Ecole Polytechnique de Montreal,, Montreal, H3C 3A7,, QC,, Canada.
Pharm Stat. 2016 Jan-Feb;15(1):15-27. doi: 10.1002/pst.1721. Epub 2015 Nov 5.
In prior works, this group demonstrated the feasibility of valid adaptive sequential designs for crossover bioequivalence studies. In this paper, we extend the prior work to optimize adaptive sequential designs over a range of geometric mean test/reference ratios (GMRs) of 70-143% within each of two ranges of intra-subject coefficient of variation (10-30% and 30-55%). These designs also introduce a futility decision for stopping the study after the first stage if there is sufficiently low likelihood of meeting bioequivalence criteria if the second stage were completed, as well as an upper limit on total study size. The optimized designs exhibited substantially improved performance characteristics over our previous adaptive sequential designs. Even though the optimized designs avoided undue inflation of type I error and maintained power at ≥ 80%, their average sample sizes were similar to or less than those of conventional single stage designs.
在之前的研究中，该团队证明了交叉生物等效性研究有效自适应序贯设计的可行性。在本文中，我们扩展了先前的工作，以在受试者内变异系数的两个范围（10 - 30%和30 - 55%）内，针对70 - 143%的一系列几何平均试验/参比制剂比率（GMR）优化自适应序贯设计。这些设计还引入了一个无效性判定标准，即在第一阶段后，如果完成第二阶段达到生物等效性标准的可能性足够低，则停止研究，同时设定了总研究规模的上限。与我们之前的自适应序贯设计相比，优化后的设计展现出显著改善的性能特征。尽管优化后的设计避免了I型错误的过度膨胀，并将检验效能维持在≥80%，但其平均样本量与传统单阶段设计相似或更小。
